Navigation systems assist users in precisely locating objects. For instance, navigation systems are used in industrial, aerospace, and medical applications. In the medical field, navigation systems assist surgeons in precisely placing surgical instruments relative to a target site in a patient. The target site usually requires some form of treatment, such as tissue removal. Conventional navigation systems employ a localizer that cooperates with trackers to provide position and/or orientation data associated with the surgical instrument and the target site, e.g., the volume of bone to be removed. The localizer is usually placed so that it has a field of view of the trackers. The trackers are fixed to the surgical instrument and to the patient to move in concert with the surgical instrument and the patient. The tracker attached to the patient is often attached to the bone being treated thereby maintaining a rigid relationship with respect to the target site owing to the rigid nature of the bone. By using separate trackers on the surgical instrument and the patient, the treatment end of the surgical instrument can be precisely positioned at the target site.
Often, retractors or other physical objects are located near the target site that should be avoided during the surgery. These retractors or other physical objects could be tracked in the same manner as the surgical instrument, e.g., using separate trackers, but adding trackers to the retractors and other physical objects can substantially increase costs and complexity in the navigation system, particularly by increasing the number of objects to be tracked by the localizer. Furthermore, since these physical objects are usually capable of movement relative to the trackers associated with the instrument and the patient, these additional physical objects aren't easily referenced to such trackers. It has been proposed to track these additional physical objects using object recognition techniques in images captured by a video camera attached to the localizer or otherwise fixed relative to the localizer. This approach, however, can be computationally expensive and difficult.
During robotic surgery, particularly when a robotic device is operating autonomously, avoidance of such physical objects is difficult when the navigation system is unable to identify the locations of all the physical objects near the target site. As a result, robotic devices are currently controlled to monitor for collisions with such physical objects and shut down in the event of a collision, relying, for instance, on feedback from a force/torque sensor to indicate a collision. However, waiting until a collision occurs before shutting down the robotic device is undesirable and results in damage to tools or the potential for endangering the patient with debris that may be created by such collisions, e.g., when rotary burs or saws hit retractors. Collisions with physical objects can delay the surgical procedure. Such delays can prolong the period in which patients are subjected to general anesthesia or otherwise increase risks associated with the surgical procedure.
Thus, there is a need in the art for systems and methods that address the identification and tracking of physical objects during robotic surgery.